class_docstr: Input is the dy and output is the dx.
  Use the function.backward in the forward_impl.
  Use the function.forward in the backward_impl.
class_docstr_tok: ["Input","is","the","dy","and","output","is","the","dx",".","Use","the","function.backward","in","the","forward_impl",".","Use","the","function.forward","in","the","backward_impl","."]
code: def __init__(
      self,
      ctx,
      kernel,
      stride=None,
      ignore_border=True,
      pad=None,
      channel_last=False,
  ):
      super(MaxPoolingBackwardDataGrad, self).__init__(ctx)
      self._func = _F.MaxPoolingBackward(
          ctx, kernel, stride, ignore_border, pad, channel_last
      )
  
file_path: nnabla/python/src/nnabla/backward_function/max_pooling_backward.py
imports: import nnabla
  import nnabla.function
  from nnabla.function import PythonFunction
label_desc: Use image node_id 1 to create a new MaxPoolingBackwardDataGrad object from inherited base classes: PythonFunction with example: obj = MaxPoolingBackwardDataGrad(ctx, kernel, stride, ignore_border, pad, channel_last)